Leveraging an Informatics Approach to Identify an Unmet Clinical Need for BRCA1/2 Testing Among Patients With Ovarian...

Area of Science:

• Oncology
• Genetics
• Medical Informatics

Background:

• BRCA1/2 testing significantly improves outcomes in ovarian cancer patients.
• Current utilization of BRCA testing in ovarian cancer remains suboptimal, necessitating scalable solutions for improved genomic care.
• Identifying patients who have undergone BRCA testing is crucial for guiding treatment decisions.

Purpose of the Study:

• To develop and apply a Natural Language Processing (NLP) pipeline to assess BRCA testing status in ovarian cancer patients.
• To evaluate BRCA testing utilization across different sites within a National Cancer Institute Comprehensive Cancer Center.
• To identify disparities and gaps in genetic testing and referral documentation.

Main Methods:

• A Natural Language Processing (NLP) pipeline was created to extract BRCA testing information from electronic medical records.
• The pipeline was applied to 308 ovarian cancer patients treated between 2017 and 2019 at a comprehensive cancer center and its network sites.
• Patient characteristics and testing utilization were compared between main campus and clinical network sites.

Main Results:

• Overall BRCA testing uptake was approximately 78%, with no significant difference between main campus and network sites.
• Testing rates increased over time (67% to 85%) and were higher in younger patients and Hispanic patients compared to White and Asian patients.
• Documentation of genetics referral for BRCA carriers was significantly lower at network sites (31%) compared to the main campus (94%).

Conclusions:

• The NLP pipeline effectively assessed BRCA testing use in ovarian cancer patients, demonstrating its potential as a scalable informatics solution.
• Despite high testing rates, 22% of patients lacked documented genetic testing, and referral documentation for BRCA carriers was notably low at network sites.
• Addressing identified gaps in genetic testing and referral is essential for timely and optimal treatment interventions in ovarian cancer care.